Mike East

A Primer on How to Spell AI

The advantage of true AI-driven analytics and why it matters

Over the past several years artificial intelligence (AI) has been one of the trendiest buzzwords around – infiltrating our lives from the movies to TV game shows like Jeopardy to software. AI is such an overloaded term, we have lost sight in what it actually means and what problems it solves. Amid this confusion it has become a marketing buzzword that just dresses up legacy products and concepts.

So what is AI? The Oxford Dictionary defines AI as:

The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

In the analytics space, there are three main concepts: Business Intelligence (BI), Machine Learning (ML), and Artificial Intelligence. Let’s explore what these really mean.

Business Intelligence – Mining structured data to develop insights based on a predetermined set of queries. Ex. Mining of seasonal usage statistics.
Machine Learning: Recognizing patterns in data. Ex. Detect anomalies in standard usage patterns.
Artificial Intelligence: Answering questions you didn’t know you even had or couldn’t anticipate.

Time and time again, monitoring products and dashboards that are traditional BI products are rebranded as AI-driven. This is not what AI is about. Building an AI solution is no small feat. It requires tons of data to build, train, and score models along with tremendous amounts of compute that is enabled by the cloud.

This is where DataCore has a significant advantage. With telemetry data based on 10,000+ production customer deployments that spans the better part of a decade, our ability to develop true AI-driven analytics is built into the foundation of the DataCore Insights Services (DIS) platform, differentiating DIS from others.

Typically, there is a chicken and egg problem in this space:

  • A company needs to launch a product to get telemetry data
  • A critical mass of telemetry data is then needed to provide value back to the customer

In the best case scenarios, companies are several years away from being able to do “real” AI. This barrier to entry is why many companies will try to brand something and AI-driven when it actually isn’t.

DIS is at the Forefront of the AI Revolution!

The AI engine in DIS provides predictive capabilities that help to ensure your storage infrastructure is achieving maximum performance and uptimes at the lowest cost. If you aren’t already using DIS, take the Guided Tour and register today at dis.io.

Get a Live Demo

Talk with a solution advisor about how DataCore SDS can make your storage infrastructure modern, performant, and flexible.

Request Live Demo

Related Posts
 
Brian Nason
The Power of Shell
Microsoft PowerShell can be an extremely useful tool for automating system management tasks in Windows. While most system configuration and administration tasks are typically done…
 
Darius Shafie
Breaking the Barriers of Physical Hardware with System Managed Mirroring
Virtualization is the DNA of DataCore. A pioneer of software-defined storage (SDS), DataCore started breaking through physical barriers that kept storage isolated in silos as…
 
DataCore 2019: A Year in Review
As 2019 comes to an end, it’s time to reflect on what the past year has meant for DataCore. We began the year with the…